Core Engineering Team

Company Description :

Redstocks Technology LLP is a Quant-as-a-Service (QaaS) platform that supports mid-tier brokers in India by providing sophisticated trading algorithms. Our platform offers optimization tools for risk management, personalized trade recommendations, and portfolio adjustments as a customizable, white-labeled solution. By continually collecting trade data, equity holdings, and market behavior patterns, we enhance the accuracy and effectiveness of our algorithms over time. This creates a self-improving feedback loop that sets us apart. Our revenue model includes licensing our technology and taking a cut of the trades executed through our system, positioning us as the tech backbone for the next generation of data-driven broking.

Role Description :

undergraduate students (1st to final year)

• Quantitative Modeling & Algorithmic Trading
• Backend/Infra Engineering (APIs, real-time systems)
• Machine Learning (prediction, signal enhancement)
• Systems Architecture & Deployment

Overview :

• Commitment

  : 10–15 hours/week

• Mode

  : Remote / Hybrid

• Duration

  : 6 months minimum

• Incentive

  : ESOPs granted after 6 months based on contribution and intent to stay

• Work With

  : Founders and core contributors, directly impacting product and pilot rollouts

high-responsibility, high-reward opportunity

Minimum Qualifications :

• Currently pursuing a

  B.Tech / B.Sc / Integrated Program

  in Computer Science, Mathematics, Data Science, Engineering, or related fields (1st to Final year).
• Strong understanding of

  at least one programming language

  (Python, C++, Rust, or Go preferred).
• Familiarity with

  Git/GitHub

  , version control workflows, and collaborative development.
• Ability to dedicate

  10–15 hours per week

  consistently for 6 months.
• Willingness to

  learn independently

  and contribute to production-grade systems.

Preferred (Bonus) Qualifications :

• Prior experience in

  backend development

  ,

  APIs

  , or working with

  Docker/Kubernetes

  .
• Exposure to

  algorithmic trading

  ,

  quant research

  , or financial systems (even as hobby projects).
• Hands-on with ML frameworks (e.g., PyTorch, TensorFlow, or Scikit-learn) or backtesting libraries.
• Familiarity with

  low-latency architecture

  or high-frequency data handling.
• Strong written documentation habits, or experience contributing to open-source projects.

Who should apply ?

• Students who’ve

  built side projects

  ,

  won hackathons

  , or contributed to live systems.
• Those looking for

  deep, real-world engineering experience

  and not just resume lines.
• People who care about building something that can scale across India's fintech landscape.